Zsuzsanna Liptak

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fotoZsLiptak, October 22, 2017
Position
Associate Professor
Academic sector
INF/01 - INFORMATICS
Research sector (ERC)
PE6_6 - Algorithms, distributed, parallel and network algorithms, algorithmic game theory

PE6_13 - Bioinformatics, biocomputing, and DNA and molecular computation

PE6_4 - Theoretical computer science, formal methods, and quantum computing

Office
Ca' Vignal 2,  Floor 1,  Room 79
Telephone
+39 045 802 7032
E-mail
zsuzsanna|liptak*univr|it <== Replace | with . and * with @ to have the right email address.
Personal web page
http://profs.scienze.univr.it/~liptak

Office Hours

Tuesday, Hours 10:00 AM - 12:00 PM,   Ca' Vignal 2, Floor 1, room 79

Curriculum

Mi occupo di bioinformatica algoritmica, e di algoritmi e strutture dati per stringhe. Quella degli algoritmi per stringhe è un'area classica dell'informatica, che di recente ha avuto nuove e importanti applicazioni nell'ambito di bioinformatica. Stringhe e sequenze, cioé dati di forma testuale, appaiono ovunque nella vita quotidiana (sequenze biologiche, pagine web, email, libri elettronici, sequenze musicali, ecc.)

Mi interessano le soluzioni applicabili a dati biologici, ma molti modelli studiati hanno importanza anche per l'area della combinatorica delle parole e nell'ambito della ricerca teorica su stringhe/sequenze.

Parte della mia ricerca si è concentrata su vari problemi algoritmici che si presentano nell'interpretazione di dati di spettrometria di massa di campioni biologici. Un'altra area di cui mi sono occupata è quella della definizione di distanze tra sequenze non basate su allineamento, e le loro applicazioni allo studio di sequenze genomiche di tipo EST e di sequenze ottenute con le nuove tecnologie nanopore.  

Sono autrice di numerosi articoli apparsi in prestigiose riviste internazionali (es. Bioinformatics, TCS, Algorithmica) ed in atti di convegni internazionali di riferimento nella mia area di ricerca. Sono inoltre regolarmente membro dei comitati scientifici di alcune tra le principali conferenze internazionali nell'area della ricerca algoritmica in bioinformatica (WABI), e string matching ed information retrieval (CPM, SPIRE, IWOCA). 
 

 

Modules

Modules running in the period selected: 29.
Click on the module to see the timetable and course details.

Course Name Total credits Online Teacher credits Modules offered by this teacher
Master's degree in Medical Bioinformatics Computational Analysis of Genome-Scale Sequences (2022/2023)   6    6 
Bachelor's degree in Bioinformatics Discrete Biological Models (2022/2023)   6    4  (Teoria)
Master's degree in Medical Bioinformatics Fundamental algorithms for Bioinformatics (2022/2023)   12  eLearning 6  (Bioinformatics algorithms)
1  (Algorithm design)
PhD in Computer Science The human olfactory system (2022/2023)   50  eLearning 1 
Master's degree in Medical Bioinformatics Computational analysis of genomic sequences (2021/2022)   6  eLearning 6 
Master's degree in Medical Bioinformatics Fundamental algorithms for Bioinformatics (2021/2022)   12  eLearning 6  (Bioinformatics algorithms)
6  (Algorithm design)
PhD in Computer Science Advanced Data Structures for Textual Data (2021/2022)   3    3 
Master's degree in Medical Bioinformatics Computational analysis of genomic sequences (2020/2021)   6  eLearning 6 
Master's degree in Medical Bioinformatics Fundamental algorithms for Bioinformatics (2020/2021)   12  eLearning 3  (Algorithm design)
6  (Bioinformatics algorithms)
Master's degree in Medical Bioinformatics Computational analysis of genomic sequences (2019/2020)   6    6 
Master's degree in Medical Bioinformatics Fundamental algorithms for Bioinformatics (2019/2020)   12  eLearning 6  (Bioinformatics algorithms)
PhD in Computer Science The human olfactory system (2019/2020)   50  eLearning 1 
Master's degree in Mathematics SageMath (2019/2020)   1     
Bachelor's degree in Applied Mathematics SageMath (2019/2020)   1     
Master's degree in Medical Bioinformatics Computational analysis of genomic sequences (2018/2019)   6    6 
Master's degree in Medical Bioinformatics Fundamental algorithms for Bioinformatics (2018/2019)   12  eLearning 6  (Bioinformatics algorithms)
Master's degree in Medical Bioinformatics Computational analysis of genomic sequences (2017/2018)   6    6 
Master's degree in Medical Bioinformatics Fundamental algorithms for Bioinformatics (2017/2018)   12  eLearning 6  (Bioinformatics algorithms)
Master's degree in Medical Bioinformatics Computational analysis of genomic sequences (2016/2017)   6    6 
Master's degree in Medical Bioinformatics Fundamental algorithms for Bioinformatics (2016/2017)   12  eLearning 6  (Bioinformatics algorithms)
Master's degree in Molecular and Medical Biotechnology Algorithms for computational biology (2015/2016)   6    6 
Master's degree in Bioinformatics and Medical Biotechnology Algorithms and programming languages for bioinformatics (2014/2015)   12    6  ALGORITMI PER BIOINFORMATICA
Bachelor's degree in Bioinformatics Discrete Biological Models (2014/2015)   6    6 
Master's degree in Bioinformatics and Medical Biotechnology Algorithms and programming languages for bioinformatics (2013/2014)   12    6  ALGORITMI PER BIOINFORMATICA
Master's degree in Bioinformatics and Medical Biotechnology Algorithms and programming languages for bioinformatics (2012/2013)   12    6  ALGORITMI PER BIOINFORMATICA
Master's degree in Bioinformatics and Medical Biotechnology Algorithms and programming languages for bioinformatics (2011/2012)   12    6  ALGORITMI PER BIOINFORMATICA

 
 

Research groups

Algorithms
The group investigates structural aspects of fundamental problems in Computer Science and their mathematical models. This leads to the design of better algorithms protocols and systems as well as understanding of their implicit computational limits. Specific areas of interests include: algorithm design, data structures, string algorithms, computational complexity, combinatorial optimization, coding and information theory, machine learning. Most results obtained are in the intersection of algorithmics with several other areas in theory and applications, including bioinformatics, communication networks, operating research and artificial intelligence.
Algorithmic Bioinformatics and Natural Computing
Application of theoretical methods and data analysis to model information underlying biological processes: graph and string algorithms for systems biology; advanced data structures for sequence data; distance measures for biological sequences; natural (biotechnological, membrane) computing; pattern recognition, machine learning for biomedical data.
Bioinformatics and Natural Computing
Algorithmic analysis of biological processes.
Research interests
Topic Description Research area
String algorithms Algorithms and data structures for strings; indexing for string problems; exact pattern matching, approximate pattern matching, string distance measures, storage, compression; problems arising in applications of strings such as computational biology, web data, textual data, big data, musical analysis; string combinatorics,combinatorics on words. Theory of computation
Design and analysis of algorithms
Algorithmic bioinformatics We develop algorithms for discrete problems arising from computational biology, among these: algorithms for mass spectrometry data interpretation, clustering of transcriptomic data, non-alignment based sequence comparison. Bioinformatics and medical informatics
Life and medical sciences


Organization

Department facilities